Assimilating electronic tagging, oceanographic modelling, and fisheries data to estimate movements and connectivity of swordfish in the North Atlantic. (25th June 2019)

• Record Type: Journal Article
• Authors: Braun, Camrin D; Gaube, Peter; Afonso, Pedro; Fontes, Jorge; Skomal, Gregory B; Thorrold, Simon R
• Editors: Kaplan, David
• Is Part Of: ICES journal of marine science. Volume 76:Number 7(2019)
• Page Start: 2305
• Page End: 2317
• Publication Date: 2019-06-25
• Subjects: movement ecology -- oceanography -- satellite telemetry -- state-space model; Ocean -- Periodicals; Fisheries -- Periodicals; Fishes -- Periodicals; Marine biology -- Bibliography -- Periodicals; 551.4605
• DOI: 10.1093/icesjms/fsz106
• Languages: English
• ISSNs: 1054-3139

Abstract

Abstract: Broadbill swordfish ( Xiphias gladius ) is a key species in commercial fisheries, but management efforts continue to be hindered by data gaps in their basic biology, including ongoing debate over stock boundaries and movement between management zones. We deployed 20 pop-up satellite archival transmitting (PSAT) tags on juvenile swordfish in the Azores and adults in the northwest Atlantic (NWA). We applied a recently developed geolocation approach that synthesizes tag data with a global observation-assimilating ocean model to improve geolocation accuracy. Resulting tracks from 16 individuals averaged 3751 km (range 345–7247 km) over 93 days (range 17–181 days). Juveniles tagged in the Azores made regional movements while adults tagged in the NWA moved between summer foraging grounds near the Grand Banks to winter habitats near the Antillean Arc. All individuals spent considerable time in the mesopelagic zone during the day, and this behaviour increased with fish size. We integrate results from our PSAT-based movements with conventional tag and catch-per-unit effort data, which indicates complex stock structure within the North Atlantic that largely supports current stock boundaries. Our work demonstrates the utility in synthesizing fishery-independent electronic tag data and fisheries datasets to improve our understanding of large pelagic fish ecology.